An assumption to compute unbiased estimated breeding values (EBV) is that all information, i.e. genomic, pedigree and phenotypic information, has to be considered simultaneously. However, current ... [more ▼]

An assumption to compute unbiased estimated breeding values (EBV) is that all information, i.e. genomic, pedigree and phenotypic information, has to be considered simultaneously. However, current developments of genomic selection will bias evaluations because only records related to selected animals will be available. The single step genomic evaluation (ssGBLUP) could reduce pre-selection bias by the combination of genomic, pedigree and phenotypic information which are internal for the ssGBLUP. But, in opposition to multi-step methods, external information, i.e. information from outside ssGBLUP, like EBV and associated reliabilities from Multiple Across Country Evaluation which represent a priori known phenotypic information, are not yet integrated into the ssGBLUP. To avoid multi-step methods, the aim of the study was to assess the potential of a Bayesian procedure to integrate a priori known external information into a ssGBLUP by considering simplifications of computational burden, a correct propagation of external information and no multiple considerations of contributions due to relationships. To test the procedure, 2 dairy cattle populations (referenced by “internal” and “external”) were simulated as well as milk production for the first lactation of each female in both populations. Internal females were randomly mated with internal and 50 external males. Genotypes of 3000 single-nucleotide polymorphisms for the 50 males were simulated. A ssGBLUP was applied as the internal evaluation. The external evaluation was based on phenotypic and pedigree external information. External information integrated into the ssGBLUP consisted to external EBV and associated reliabilities of the 50 males. Results showed that rank correlations among Bayesian EBV and EBV based on the joint use of external and internal data and genomic information were higher than 0.99 for the 50 males and internal animals. The respective correlations for the internal evaluation were equal to 0.50 and 0.90. Thereby, the Bayesian procedure can integrate external information into ssGBLUP. [less ▲]

Milk composition in fatty acids (FA) portrays a class of novel traits of interest for both human health and animal robustness. With the exception of Wallonia, Luxembourg is currently the only place in the ... [more ▼]

Milk composition in fatty acids (FA) portrays a class of novel traits of interest for both human health and animal robustness. With the exception of Wallonia, Luxembourg is currently the only place in the world where, using mid-infrared spectrometry, milk composition in 29 FA is routinely recorded for dairy cows. Since 2007, spectral data has been recorded so far on 87,368 cows from 690 different herds, by 2 main control methods (T-method: one sample of only one milking, morning or evening, and S-method: proportionate sample of all daily milkings). Additionally, milk, fat and protein yields are available since 1990. The availability of FA allows many options for management use and animal breeding but requires advanced modeling (e.g., adapted to the testing methods). In the context of animal breeding, genomic selection has been widely developed in dairy cattle, where single-step approach (ssGBLUP) is particularly well suited for small-sized populations, as the dairy cattle population of Luxembourg (365,892 animals currently in pedigree) and is completely integrated into mixed modeling of phenotypic data. The objectives of this study were: (1) to assess the potential benefits of a single-step genomic evaluation on milk FA composition in a small-sized population and in particular (2) to quantify the impact of genomic information on reliability (REL) of estimated breeding values (EBV) of FA in Luxembourg. In a preliminary study for a single FA, oleic acid (C18:1 cis 9) genetic evaluations were performed on 47,613 milk records; collected by S-method, from 8,000 cows in first parity with a random regression test-day model using second order Legendre polynomials. For this sample, molecular data was simulated for 422 AI sires, ancestors of recorded cows. Prediction error variances (PEV) were used to compute REL and effective daughter contributions (EDC). First results showed a low increase in REL and EDC. Extension of this research to all sampling methods and research on the optimum structure of the reference population (bulls, cows) will be done to fit the Luxembourg-specific situation. [less ▲]

A particularity of the Luxembourg milk recording is the use of different schemes. Two principal schemes are applied: the scheme “S” applied on 69.1% of the total herds (n=712) and consisting in one ... [more ▼]

A particularity of the Luxembourg milk recording is the use of different schemes. Two principal schemes are applied: the scheme “S” applied on 69.1% of the total herds (n=712) and consisting in one proportionate sample of all daily milkings, and the scheme “T” (21.6% of the total herds) which consists in one sample of only one milking (morning or evening milking) (and alternating milking time from month to month). The problematic is that application of different schemes could influence the milk components (protein and fat yield) and the milk fat components (saturated and unsaturated groups of fatty acids) genetic parameters estimation and to prevent all comparisons between dairy population under different milk recording schemes. A total of 47,613 and 44,833 test-day records were obtained, respectively for schemes “S” and “T” from Holstein cows in first lactation in Luxembourg dairy herds. The used model included as fixed effects: herd x date of test, class of age, and month x year. Random effects were permanent environmental, additive genetics, and residual effects. The main objective of this work is to study the effect the choice of milk recording schemes (“S” or “T” schemes) on milk yield and milk components genetic parameters. A solution could be to add a fixed effect taking in account the milking time. The second objective is to study the effect of milking time (morning or evening) on genetic parameters estimated in the case of scheme “T”. According to the results, genetic parameters were statistically different between the schemes “S” and “T” for milk yield (P value < 0.0001). Further, the classifications of bulls according to their breeding values were very different when values were estimated on basis of scheme “S” or “T” (Spearman correlation value of 0.51 for milk yield for example). In conclusion, using several milk recording schemes do not allow any comparison of genetic parameters between dairy cattle’s. [less ▲]

Dairy production is pointed out for its large methane emission. Therefore, specific nutritional strategies are applying to abate methane emission but very less information is available about the animal ... [more ▼]

Dairy production is pointed out for its large methane emission. Therefore, specific nutritional strategies are applying to abate methane emission but very less information is available about the animal genetic variability of methane emission. Methane indicators using traits indirectly related to methane and easily recorded like the mid-infrared (MIR) prediction of fatty acid could be used to conduct genetic studies. MIR methane indicators used in this study were derived from published fatty acid based methane indicators using 597 calibration samples. Genetic parameters of these MIR indicators were estimated by single trait random regression test-day models from 13,389 records collected on 1602 Dual Purpose Belgium Blue cows in their first 3 lactations. For the published indicator showing the highest relationship (R2 =0.88) with Sulphur hexafluoride (SF6) methane emission data, the average daily heritability was 0.25±0.06, 0.25±0.07 and 0.18±0.09 for the first three lactations, respectively. Similarly, the lactation heritability was 0.45±0.09, 0.46±0.11 and 0.24±0.14. The sire genetic variability was 3.60, 4.08, 1.19 kg2 of methane for the first three lactation, respectively. The genetic difference between the sires having cows eructing the highest and the lowest methane content was 11.62, 13.01 and 5.98 kg per lactation for the first three parities. This study suggested that methane indicator traits can be predicted by MIR and the genetic variability of these traits seems to exist. Therefore, it also suggests the genetic variability of methane content eructed by dairy cows. These first finding might open new opportunities for animal selection program on methane emission. [less ▲]

Currently the Walloon Region of Belgium is one of the first regions in the World where mid-infra red (MIR) spectral data is recorded in routine for nearly all cows under milk recording. Based on this data ... [more ▼]

Currently the Walloon Region of Belgium is one of the first regions in the World where mid-infra red (MIR) spectral data is recorded in routine for nearly all cows under milk recording. Based on this data, in some herds collected since 2007, saturated (SFA) and monounsaturated fatty acid (MUFA) contents in milk are predicted for each test-day. Together with correlated traits as milk, fat and protein yields, estimated breeding values (EBV) are now computed in routine for SFA and MUFA starting in June 2012. A total of 499 821, 392 255, 277 465 fatty acid records were available in first, second and third lactation for this run. A restricted selection index, called NQI (nutritional quality index) was developed that puts a negative weight on SFA, a positive weight on MUFA and restricts changes in milk and fat yields to zero. By using this index for a constant fat content, milk fat will be selected to be less saturated with a high contribution from MUFA. Based on this system a single-step genomic evaluation is under development including the introduction of MACE breeding values for correlated traits. The final step is to offer for owners of genotyped animals, a service to provide them with genomically enhanced NQI. Similar systems are under development in Wallonia for other novel traits (e.g., methane emissions) based on the ability to predict them from MIR spectral data. [less ▲]

Currently the Walloon Region of Belgium is one of the first regions in the World where mid-infra red (MIR) spectral data is recorded in routine for nearly all cows under milk recording. Based on this data ... [more ▼]

Currently the Walloon Region of Belgium is one of the first regions in the World where mid-infra red (MIR) spectral data is recorded in routine for nearly all cows under milk recording. Based on this data, in some herds collected since 2007, saturated (SFA) and monounsaturated fatty acid (MUFA) contents in milk are predicted for each test-day. Together with correlated traits as milk, fat and protein yields, estimated breeding values (EBV) are now computed in routine for SFA and MUFA starting in June 2012. A total of 499 821, 392 255, 277 465 fatty acid records were available in first, second and third lactation for this run. A restricted selection index, called NQI (nutritional quality index) was developed that puts a negative weight on SFA, a positive weight on MUFA and restricts changes in milk and fat yields to zero. By using this index for a constant fat content, milk fat will be selected to be less saturated with a high contribution from MUFA. Based on this system a single-step genomic evaluation is under development including the introduction of MACE breeding values for correlated traits. The final step is to offer for owners of genotyped animals, a service to provide them with genomically enhanced NQI. Similar systems are under development in Wallonia for other novel traits (e.g., methane emissions) based on the ability to predict them from MIR spectral data. [less ▲]

Livestock is considered as an important contributor to global methane emissions, predominately due to methanogenesis from ruminants. Moreover, these emissions also represent major losses of energy for ... [more ▼]

Livestock is considered as an important contributor to global methane emissions, predominately due to methanogenesis from ruminants. Moreover, these emissions also represent major losses of energy for dairy cows and therefore are linked to production efficiency. The on-going development of predictive equations (e.g., from milk composition) would allow to relate methane emissions to farm management (e.g., nutrition, environment) on a large scale in the Walloon Region of Belgium. Finally, by acquiring improved knowledge of these relationships, contributions to mitigate methane emissions could be based on an improved management of dairy herds. [less ▲]

The genetic parameters of CH4 indicators were estimated by single trait test-day models from 16,825 records collected on Walloon Dual Purpose Belgium Blue cows in their first 3 lactations. Fatty acid based CH4 indicators published in the literature were predicted from milk mid-infrared spectra using 597 calibration samples. For the indicator showing the highest link (R2 =0.88) with SF6 CH4 data, the average daily heritability was 0.21, 0.20 and 0.10 for each lactation, respectively. The sire genetic variability was on average 2.82 kg2 of CH4 per lactation. The genetic difference between the sires having cows eructing higher and lower CH4 was 10 kg of CH4 averaged per lactation. In conclusion, CH4 indicators can be predicted by MIR and the genetic variability of these traits seems to exist. [less ▲]

Improving dairy cow fertility by means of genetic selection has become increasingly important over the last years in order to overcome the declining cow fertility. This study investigated whether the ... [more ▼]

Improving dairy cow fertility by means of genetic selection has become increasingly important over the last years in order to overcome the declining cow fertility. This study investigated whether the fatty acids profile in milk could be used as an early predictor of genetic merit for fertility. Genetic covariances among 17 fatty acid contents in milk and the number of days from calving to conception were estimated from 29,792 first-parity Holstein cows. Results substantiated the unfavorable relationship among fertility and body fat mobilization in early lactation. Also, about 75% of the genetic variability of fertility was explained by the variability in milk fatty acids profile over the lactation indicating that these traits could be used to supplement genetic evaluations for fertility. [less ▲]

For more than a decade, high losses of honey bee colonies have been noticed in several countries, including Belgium. Currently often the mite Varroa destructor is considered a main threat for beekeeping ... [more ▼]

For more than a decade, high losses of honey bee colonies have been noticed in several countries, including Belgium. Currently often the mite Varroa destructor is considered a main threat for beekeeping. In view of the inefficiency of the current chemical treatments, one of the solutions is to select honey bees tolerant to this parasite using genomic selection. To reach this objective the genetic diversity of honey bees needs first to be studied using mainly ‘Single Nucleotide Polymorphisms’ (SNP). Records and samples will be collected all over the Walloon Region in order to create an informative phenotypic and genomic data base that will be used for ‘Genome Wide Association Studies’ (GWAS) to detect associations between SNPs and tolerance, and to select bees tolerant to Varroa destructor. [less ▲]

The main objective of this study was to analyze milking-to-milking variability of milk yield and milk composition (such as fat and protein percentages and somatic cell count). Additional objective was to ... [more ▼]

The main objective of this study was to analyze milking-to-milking variability of milk yield and milk composition (such as fat and protein percentages and somatic cell count). Additional objective was to extend this analyze to the milk fat composition. Milk samples (n=195.960) were collected from 29.636 cows in 491 Luxembourg farms and analyzed by MIR spectrometry. The milk contents of saturated, mono-, poly- and unsaturated fatty acids, and short, medium and long chain fatty acids were predicted from the recorded MIR spectral data. As expected, the milk composition and the milk fat composition, are affected by several factors as the milking period and the days in milk. In practice, using separately milk evening and milk morning could be interesting for cheese or butter production. [less ▲]

One of the most important theoretical assumptions of methods used to assess genetic values is that all available information has to be considered simultaneously to obtain unbiased estimates. However, the ... [more ▼]

One of the most important theoretical assumptions of methods used to assess genetic values is that all available information has to be considered simultaneously to obtain unbiased estimates. However, the widespread international exchange of genetic material and, more recently, the important development of the genomic selection lead to the coexistence of different genetic evaluations. Therefore, the blending of the different sources of information is necessary to achieve better prediction. Integration of external information into genetic evaluations by a Bayesian procedure can partially resolve the problem under some assumptions. Results from such a method that also avoids double counting among external animals are highly similar to those from a joint evaluation. [less ▲]

The objective of this study was to estimate the genetic relationships between days open (DO) and both milk production traits and fatty acid (FA) content in milk predicted by mid-infrared spectrometry. The ... [more ▼]

The objective of this study was to estimate the genetic relationships between days open (DO) and both milk production traits and fatty acid (FA) content in milk predicted by mid-infrared spectrometry. The edited data set included 143,332 FA and production test-day records and 29,792 DO records from 29,792 cows in 1,170 herds. (Co)variances were estimated using a series of 2-trait models that included a random regression for milk production and FA traits. In contrast to the genetic correlations with fat content, those between DO and FA content in milk changed considerably over the lactation. The genetic correlations with DO for unsaturated FA, monounsaturated FA, long-chain FA, C18:0, and C18:1 cis-9 were positive in early lactation but negative after 100 d in milk. For the other FA, genetic correlations with DO were negative across the whole lactation. At 5 d in milk, the genetic correlation between DO and C18:1 cis-9 was 0.39, whereas the genetic correlations between DO and C6:0 to C16:0 FA ranged from -0.37 to -0.23. These results substantiated the known relationship between fertility and energy balance status, explained by the release of long-chain FA in early lactation, from the mobilization of body fat reserves, and the consequent inhibition of de novo FA synthesis in the mammary gland. At 200 d in milk, the genetic correlations between DO and FA content ranged from -0.38 for C18:1 cis-9 to -0.03 for C6:0. This research indicates an opportunity to use FA content in milk as an indicator trait to supplement the prediction of genetic merit for fertility. [less ▲]